Senior Software Engineer - ML Infrastructure · Plaid

Fri, 24 Apr 2026 16:09:59 GMT
Engineering

Plaid · San Francisco · $190,800-$286,800 per year · hybrid

We believe that the way people interact with their finances will drastically improve in the next few years. We're dedicated to empowering this transformation by building the tools and experiences that thousands of developers use to create their own products.

Plaid powers the tools millions of people rely on to live a healthier financial life. We work with thousands of companies like Venmo, SoFi, several of the Fortune 500, and many of the largest banks to make it easy for people to connect their financial accounts to the apps and services they want to use.

As a Senior Software Engineer on the Machine Learning Infrastructure team, you will design, build, and operate the systems that power machine learning across Plaid. You will apply your deep technical expertise to create scalable, reliable, and secure ML platforms, and collaborate closely with ML product teams to accelerate the delivery of ML & AI-powered products.

Responsibilities

Design and implement large-scale ML infrastructure, including feature stores, pipelines, deployment tooling, and inference systems.

Drive the rollout of Plaid’s next-generation feature store to improve reliability and velocity of model development.

Help define and evangelize an ML Ops “golden path” for secure, scalable model training, deployment, and monitoring.

Ensure operational excellence of ML pipelines and services, including reliability, scalability, performance, and cost efficiency.

Collaborate with ML product teams to understand requirements and deliver solutions that accelerate experimentation and iteration.

Contribute to technical strategy and architecture discussions within the team.

Mentor and support other engineers through code reviews, design discussions, and technical guidance.

Qualifications

5+ years of industry experience as a software engineer, with strong focus on ML/AI infrastructure or large-scale distributed systems.

Hands-on expertise in building and operating ML platforms (e.g., feature stores, data pipelines, training/inference frameworks).

Proven experience delivering reliable and scalable infrastructure in production.

Solid understanding of ML Ops concepts and tooling, as well as best practices for observability, security, and reliability.

Strong communication skills and ability to collaborate across teams.

Additional Information

Our mission at Plaid is to unlock financial freedom for everyone. To support that mission, we seek to build a diverse team of driven individuals who care deeply about making the financial ecosystem more equitable.